Prediction modeling in sequential flow networks

A system comprising:

• a memory;
• a processor communicatively coupled to the memory, the processor operable to execute instructions stored in the memory, the instructions causing the processor to:
• receive a plurality of input process variables and a plurality of output process variables associated with a respective plurality of processes;
• create an optimal decision tree based on the plurality of input variables, plurality of output variables, and plurality of processes;
• for each of the plurality of processes identify intermediate quality modes and corresponding controls;
• train the optimal decision tree based on the identified intermediate quality modes and corresponding controls;
• and
• provide recommended control variable values for each of the plurality of processes.

A computer program product for prediction and optimization in sequential flow networks, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer, to cause the computer to perform a method comprising:

• receiving, using a processor, a plurality of input process variables and a plurality of output process variables associated with a respective plurality of processes;
• creating, using the processor, an optimal decision tree based on the plurality of input variables, plurality of output variables, and plurality of processes;
• for each of the plurality of processes identifying, using the processor, intermediate quality modes and corresponding controls;
• training, using the processor, the optimal decision tree based on the identified intermediate quality modes and corresponding controls;
• and
• providing, using the processor, recommended control variable values for each of the plurality of processes.